标题:Automatic Identification of LAMOST Spectra with Continuum Problem Based on High Performance Computing
作者:Yu, Jingjing; Pan, Jingchang; Meng, Fanlong
通讯作者:Pan, Jingchang
作者机构:[Yu, Jingjing; Pan, Jingchang; Meng, Fanlong] Shandong Univ, Sch Mech Elect & Informat Engn, Weihai, Peoples R China.
会议名称:International Conference on Cloud Technology and Communication Engineering (CTCE)
会议日期:AUG 18-20, 2017
来源:2017 INTERNATIONAL CONFERENCE ON CLOUD TECHNOLOGY AND COMMUNICATION ENGINEERING (CTCE2017)
出版年:2017
卷:910
期:1
DOI:10.1088/1742-6596/910/1/012052
摘要:Continuum problem is a phenomenon that the continuum of spectra get off their actual continuum even break off due to interstellar extinction and flux calibration, and it will have negative impact on the subsequent process such as spectral line extraction and so on. Based on this problem and fully considering of the continuum features of the stellar spectra, a method of automatic detection and recognition of the continuum problem in the stellar spectra based on High Performance Computing (HPC) is proposed, which will improve work efficiency greatly compared with the traditional human eyes examination under the condition of maintaining high accuracy. Continuum template matching is used to identify the continuum problem spectra in this paper. The first step goes to fit continuum of the test stellar spectra and the template spectra, then the flux differences of the two continuum we fitted before at every point of wavelength in the continuum spectra will be calculated based on full spectra matching to analyze the features of its distribution. The features we count are average (called beta) value and standard deviation (called delta). The percentage of points distributed in range beta +/-alpha*delta will be detected to confirm that if there is continuum problem. Experiments was taken to identify the continuum problem spectra on HPC, which demonstrate the validity and efficiency of the method, and this has important reference value to resolve similar massive spectra data processing problems in the future.
收录类别:CPCI-S;EI
资源类型:会议论文
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